scarlet2

Main namespace for scarlet2

Classes

Scenery()	Class to hold the context for the current scene
Parameterization()	Class to hold the context for the current parameter set
Box(shape[, origin])	Bounding Box for data array
Frame(bbox[, psf, wcs, channels])	Definition of a view of the sky
Parameter(node[, name, constraint, prior, ...])	Class representing a single optimizable parameter
Parameters(base)	Collection class that contains parameters
Module()	Scarlet2 base module
Morphology()	Morphology base class
ProfileMorphology(size[, ellipticity, shape])	Base class for morphologies based on a radial profile
GaussianMorphology(size[, ellipticity, shape])	Gaussian radial profile
SersicMorphology(n, size[, ellipticity, shape])	Sersic radial profile
StarletMorphology(coeffs)	Morphology in the starlet basis
Observation(data, weights[, psf, wcs, ...])	Content and definition of an observation
CorrelatedObservation(data[, psf, wcs, ...])	Content and definition of an observation with pixel correlations
PSF()	PSF base class
ArrayPSF(morphology)	PSF defined by an image array
GaussianPSF(sigma)	Gaussian-shaped PSF
Scene(frame)	Model of the celestial scene
Component(center, spectrum, morphology)	Single component of a hyperspectral model
DustComponent(center, spectrum, morphology)	Component with negative exponential model
Source(center, spectrum, morphology)	Source model
PointSource(center, spectrum)	Point source model
Spectrum()	Spectrum base class
StaticArraySpectrum(data, bands[, band_selector])	Static (non-variable) source in a transient scene
TransientArraySpectrum(data[, epochs, ...])	Variable source in a transient scene with possible quiescent periods
Starlet(image, coefficients, generation, ...)	Wavelet transform of a images (2D or 3D) with the 'a trou' algorithm.

Functions

fit(scene, observations, *args[, schedule, ...])	Fit model parameters of every source in scene to match observations.
sample(scene, observations, *args[, seed, ...])	Sample parameters of every source in scene to get posteriors given observations.
check_fit(scene, observation)	Check the scene after fitting against the various validation rules.
check_observation(observation)	Check the observation object for consistency
check_scene(scene)	Check the scene against the various validation rules.
check_source(source)	Check the source against the various validation rules.
relative_step(x, *args[, factor, minimum])	Step size set at factor times the norm of x
set_validation([state])	Set the global validation switch.